A universal medical imaging modality translation model in brain and head-and-neck radiotherapy.

ABSTRACT:

Purpose

We developed a universal image translation model-Translate Any Modality (TAM) model to synthesize MRI sequences and CT for brain and head-and-neck radiotherapy, facilitating downstream clinical tasks including multimodal registration and treatment dose calculation.

Methods and materials

We retrospectively curated multi-modal imaging from 90 patients (43 brain, and 47 head-and-neck), each with up to eight MRI sequences and a paired CT. TAM uses a two-stage translation strategy: a 3D U-Net to firstly segment soft tissues and bones to serve as anatomical anchors; and a conditional diffusion model, guided by these masks, to synthesize the target modality from any available input modalities. We evaluated 46 MRI-to-MRI and MRI-to-CT translation tasks against two comparison

SUBMITTER: Li Y 

PROVIDER: S-EPMC12777550 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature